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2009,21(6):835-842 DOI: 10.1016/S1001-6058(08)60220-6

NUMERICAL STUDY ON SALINITY STRATIFICATION IN THE OUJIANG RIVER ESTUARY*

JIANG Heng-zhi, SHEN Yong-ming State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China, E-mail: hzjiang2005@mail.dlut.edu.cn WANG Shou-dong Transport Planning and Research Institute, Beijing 100048, China

(Received May 11, 2009, Revised August 17, 2009)

Abstract: The variations of current, salt intrusion and vertical stratification under different conditions of river flow and wind in theOujiang River Estuary (ORE) were investigated in this article using the Environmental Fluid Dynamics Code (EFDC). The model was verified against water level variation, velocity, and salinity variations in June 2005. The simulation results agreed well with measured data. Six sensitivity tests were conducted for different conditions of river flow and wind specified in the model. Modelresults show that salinity intrudes further upstream under scenarios with low flow and downriver local wind conditions. In contrast, the responses of salinity stratification to different environmental forcing functions were different in different portions of the estuary. Salinity stratification was enhanced under high flow condition. Model results also show that wind is not crucial to the salt intrusion and salinity stratification in the ORE.

Key words: salinity stratification, wind, river discharge, Oujiang River Estuary(ORE)

1. IntroductionRecently, more attention has been paid to the

salinity stratification in estuaries, where a river enters into open sea and fresh water mixes with salt water[1-3].Estuaries are highly variable in physical, chemical, and biological properties. Tides and freshwater inflows are the two major external forcing mechanisms controlling estuarine processes. The freshwater inflows produce a net seaward transport, while the tides lead to periodic seaward and landward transport. The freshwater tends to float over the denser seawater, but tidal mixing reduces this stratification. Its driving mechanism is commonly attributed to

* Project supported by the National Basic Research Program of China (973 Program, Grant No. 2006CB403302) the National Natural Science Foundation of China (Grant Nos. 50839001, 50779006). Biography: JIANG Heng-zhi (1979-), Male, Ph. D. Candidate

longitudinal baroclinic pressure gradients and the viscosity acting against it. The gravitational circulation is further influenced by factors such as earth’s rotation, local topography, river flow, salinity intrusion, tide and wind forcing[4-9].

Stratification plays a fundamental role on nutrient transport in estuaries. Analyzing the development and breakdown of stratification in estuaries will provide better understanding of the dynamical process of the estuary and its influence on living resources. In a partially stratified estuary, estuary stratification-mixing process is often regulated by its spring-neap tidal cycles. The intensity of stratification depends on the buoyancy input and the mixing produced by tidal and wind stirrings. Studies of estuarine stratification show that the freshwater buoyancy input is one of the most influential mechanisms of estuary circulation[10,11].

The Oujiang River is the second longest river in

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Zhejiang Province of China, and the Oujiang River Estuary (ORE) is a hilly, fluvial and macro-tidal estuary. Tide in the ORE is a normal semidiurnal tide with average tidal range over 4 m, and the tide is strong in the Oujiang River estuary. Tidal reach is 78 km, and the tidal limit reach extends to Wenxi[12]. The tidal current in this area is an alternating current, and the duration of flood current is shorter than that of ebb current. During the spring, summer and winter, the averaged ebb current speed is greater than the averaged flood current speed. The general circulation pattern of the ORE is dominated by wind, freshwater discharge and salinity-induced currents. Salinity stratification is mainly controlled by freshwater discharge and wind.

In order to have a better prediction of salinity stratification in the ORE, a numerical model was first verified using field data in June 2005. Then the model is applied to numerical experiments to examine current circulation, salinity intrusion and stratification responses to different river flow and wind conditions.

2. Numerical model 2.1 Model description

The model used in this study is modified from EFDC, a public-domain modeling package for simulating three-dimensional flow, transport and biogeochemical processes in surface water systems[13].This model is used to solve the three-dimensional turbulent averaged equations of motions for a variable density fluid under the vertically hydrostatic assumption. Dynamically coupled transport equations for turbulent kinetic energy, turbulent length scale and temperature are also solved. The two turbulence transport equations implement the Mellor-Yamada level 2.5 turbulence closure scheme[14]. Recent applications of the EFDC model include the effects of selective withdrawal on hydrodynamics of a stratified reservoir[15], modeling the nutrient dynamics under critical flow conditions in three tributaries of St. Louis Bay[16], and hydrodynamic processes in the St. Lucie Estuary[17], water quality and SAV modeling of a large shallow lake[18]. In China, the applications of the EFDC model include hydrodynamic numerical model of the confluence of the Yangtze River and Jialing River in Chongqing[19], hydrodynamic processes in the Wuhan catchments of the Yangtze River[20],three-dimensional hydrodynamic and water quality simulation of North Jiangsu offshore sea based on EFDC[21], and three-dimensional numerical simulation of tidal flow and salinity in the Oujiang Estuary[22].

The model equations used in the EFDC are the horizontal momentum equations and continuity equation in the stretched vertical and curvilinear horizontal coordinate system documented by

Hamrick[13]. The turbulence sub-model is used to calculate the vertical eddy viscosity and diffusivity through simulation of turbulence energy and length scale. The horizontal eddy viscosity MA is evaluated using Smagorinsky’s formula[23],

=M CA A x y

2 22 1+ + +2

u v u vx y y x

(1)

In general, the parameter CA ranges from 0.1 to 0.2. If the grid scale is enough small, CA can take the value 0. As the depth water varies acutely, it is necessary to reserve the horizontal eddy viscosity

MA . x and y are horizontal grid sizes in this model. In which, according to the grid scale,

. Vertical boundary conditions for the solution of the momentum equations are based on the specification of kinematic shear stresses,

= 0.1CA

2 2, = , = + ,xz yz bx by b l l l lC u v u v (2)

And

2 2, = , = + ,xz yz sx sy s w w w wC U V U V (3)

At the bottom, , and the free surface, = 0z= 1z , respectively, with and being the

components of the wind velocity at 10 m above the water surface. The subscript refers to velocity and elevation at the mid-point of bottom layer. The bottom drag coefficient is given by

wU wV

l

2

0

=ln

2

bl

C

z

(4)

where is the Von Karman constant, l the dimensionless thickness of the bottom layer, and 0zthe dimensionless roughness height. The wind stress coefficient is given by

2 2= 0.001 0.8 + 0.065 +as w

w

C U wV (5)

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for the wind velocity components in meters per second, with a and w denoting air and water densities respectively.

Fig.1 Topography of the ORE

Orthogonal curvilinear coordinate was used in the horizontal direction and sigma coordinate was used in the vertical direction in this model. Based on the features of the study area, a curvilinear orthogonal grid was used to represent the complex geometry of the ORE (Fig.1). The model grid consists of 2541 grid cells in the horizontal direction, with grid size ranging from 25 to 800 m in the ORE (Fig.2). The tidal forcing makes this water body well mixed vertically, except when large amount of freshwater is discharged into this area. The model has six vertical layers. Sensitivity tests with a ten-layer model indicate that the six-layer model is adequate to represent the vertical structure of the system in most of duration. Model calibration is the adjustment of model parameter values within reasonable and acceptable ranges, so that the deviations between the model results and the measured data are minimized and are within some acceptable ranges of accuracy. Model verification is the subsequent testing of a calibrated model to a second independent data set, usually under different external conditions, to further examine the model’s ability to realistically represent the water body.

Fig.2 Model grid and computed transection AB for the ORE

2.2 Model application The numerical model was applied to calculate the

salinity distribution under the combined action of river flows, tidal currents and wind force. The numerical

model was validated using the hydrographic data for 15 d obtained from several measurement stations (Fig.3)

Fig.3 Time series of modeled surface tidal elevation and measured data

The comparison of model-predicted tidal elevations and the observed data from the stations located at Jiang Xin, Long Wan, Qi Li Gang, Qing Shui Bu, Yang Fu Shan and Zhuang Yuan are shown

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Fig.4 Time series of modeled velocity, flow direction and measured data

in Fig.3. It can be seen that the model results match the observed data very well. The model-predicted high and low tidal phases are in strong agreement with observed data. The spring-neap tidal cycle and the diurnal inequality are well reproduced. The distribution of the current velocities in the estuary was affected by the combined action of river flows, tidal currents and wind. Comparisons of model-predicted

velocities and observed data at selected stations are presented in Fig.4. In general, the model-predicted velocities match the observed velocities reasonably well, especially at the high flood and ebb tides. The model tended to over-predict the low peak in velocity. The mismatch between model results and field data is most likely due to lack of exact tidal elevations data and daily freshwater discharge for the specification of the boundary conditions. However, for the purpose of simulating effluent dilution and transports, the level of accuracy in the currents simulated is considered sufficient.

Fig.5 Time series of modeled salinity and measured data

Based on the above comparisons, the numerical model appears to be a suitable choice to simulate the distribution of currents under the combined action of the freshwater discharge and the tidal currents in the ORE. Considering the significance of physical process for distribution of salinity in the critical habitats, a certain level of freshwater inflows must be maintained to meet the requirements of salinity objectives.

Figure 5 shows a comparison between the modeled and the observed values of surface and bottom salinity at 16# and 30# in June 2005, which shows that the model leads to relatively large

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discrepancies. The reasons for the discrepancies between the observed and predicted results, especially where mixture of the freshwater with the saltwater occurs, include two aspects. The first is the freshwater inflow estimation should affect the accuracy of salinity simulation, and the second is calculation of the dispersion-diffusion coefficient, which will greatly affect the calculated distribution of the salinity. Various studies of the dispersion of salinity have been conducted in these years. However, there have still been no generally accepted results[24,25]. A more detailed study of the dispersion-diffusion coefficient for salinity in an estuary is needed in the future research.

The numerical model was validated by the field data, which proved that the model was a suitable tool for simulating the distribution of salinity levels under the combined action of the river and ocean and could be used to establish relationships between freshwater inflows, wind and the ecological salinity objectives and to assess the changes in freshwater inflow and wind will affect salinity in the estuary. The deviations between the model results and the field data suggest

Fig.6 Model results of vertical-averaged salinity in flood

tidethat where complex mixing of fresh water and salt water occurs, additional research will be needed to refine the numerical model so that it can predict more accurately the situations in these areas.

Table 1 Model setting for six sensitivity tests Bottom and

surface salinity (ppt)

Flow(m3/s)

Tide(m)

Wind(m/s)

Base case 12, 10 1189 2.0 0.0

High flow 12, 10 5090 2.0 0.0

North wind 12, 10 1189 2.0 5.0

South wind 12, 10 1189 2.0 5.0

West wind 12, 10 1189 2.0 5.0

East wind 12, 10 1189 2.0 5.0

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Fig.7 Model results of vertical distributions of salinity along the transection AB in flood tide

3. Experiment design and model results 3.1 Experiment design

In order to examine the system responses to different fresh-water inflow and wind conditions in the ORE, eight model experiments were conducted, and each was run for 20 d with constant boundary conditions specified. The model configurations for the six scenarios are shown in Table 1.

The base case scenario was selected to represent the average environmental situations during June, 2005, which was forced by the M2 tide with an amplitude of 2.0 m, the fresh-water inflow with a discharge rate of 1189 m3/s and no wind. At the downstream boundary, the salinity with 12 ppt at the bottom layer and 10 ppt at the surface layer were specified. The system responses to different environmental conditions were assessed by changing one parameter from the base case in the seven other

model experiments. In June 2005, the average discharge was 1189 m3/s, and the greatest discharge was 5090 m3/s[26]. The effects of wind were examined with a 5 m/s magnitude at the directions of 0, 90, 180, 270 from north. Temperature was set to 25 for all the experiments to represent summer period. From these experiments, we can know: (1) the response of salinity distribution in the ORE to various environmental forcing, and (2) the forcing causing the salinity stratification most sensitively. 3.2 Model results 3.2.1 Base case

The model results of vertical-averaged salinity distributions in flood tide are presented in Fig.6. For the base case (Fig.6(a)), the modeled salinity reaches the place approximately 20 km upstream from the mouth of the ORE. Figure 7 shows model results of along-channel salinity distributions in ebb tide in the ORE.

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3.2.2 River discharge Under high flow conditions, the model results

show that stronger flow pushes salinity downriver (Fig.6(b)). Correspondingly, salinity stratification is much stronger than the base case (Fig.7(b)). For the base case, the model-simulated salinity intrudes further upriver. Compared to the base case, the net seaward surface flow is decreased and the net landward bottom flow remains similar. 3.2.3 Wind

Under south wind and east wind, the model results show that vertical distributions of salinity along the transection are not much too different. The west wind exerts an upriver surface shear stress which slows down the surface current. The typical gravitational estuarine circulation is primarily driven by the balance between the barotropic pressure gradient and the baroclinic density gradient [1]. The surface shear stress caused by the 5 m/s west wind acts against the downriver barotropic pressure gradient, and modulates the flow field. Consequently, the upriver intrusion of bottom salt water is inhibited. By contrast to the case of the west wind, under the east wind, the seaward surface flow is much increased (compared to the base case). The model-simulated salinity intrudes further eastward than in the base case, but salinity stratification is the same as that for the base case, south wind, north wind and west wind. (see Figs.7(a),7(c)-7(f)). Figure 8 shows that the river discharge is more important than the wind force for the salinity distribution in the ORE.

Fig.8 Model results of vertical mean of salinity along the transect AB in flood tide

4. Conclusions A numerical model has been constructed and

validated by experimental results, indicating that the numerical model is suitable for simulating the distribution of salinity under the combined action of tidal currents, freshwater inflows and wind in estuary. However, the calculation of salinity can be improved by further study of the dispersion-diffusion coefficient for salinity and by improving the simulation in areas where the mixing of freshwater and salt water becomes complex.

The most important finding of this research work is perhaps that the response of salinity distribution in the ORE to various environmental forcing is very different in different portions of the estuary. In addition, in the ORE, salinity stratification tends to be most sensitive to the changes of river discharge, while the distance of salinity intrusion is very sensitive to additional factors such as east wind. Freshwater discharge is the primary environmental factors controlling dynamics in the ORE.

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